Assessing external exposome by implementing an Environmental Data Management System using Open Data

Due to the increasing importance of exposome in environmental epidemiology, feasibility and usefulness of an Environmental Data Management System (EDMS) using Open Data was evaluated. The EDMS includes data from 10 European cities (Celje (Slovenia), Łódź (Poland), Manchester (UK), Palermo (Italy), Paris (France), Porto (Portugal), Regensburg (Germany), Reus (Spain), Rijeka (Croatia), Thessaloniki (Greece)) about external non-specific and specific exposome factors at the city or country level (2017–2020). Findings showed that the highest values of life expectancy were in Reus females (86 years) and Palermo males (81 years). UK had the highest obesity rate (28%), Croatia the highest prescribed drug consumption (62%), Greece and Portugal the highest smoking rates (37%, 42%) and daily alcohol consumption (21%), respectively. The most polluted cities were Thessaloniki for PM10 (38 µg/m3), Łódź for PM2.5 (25 µg/m3), Porto for NO2 (62 µg/m3) and Rijeka for O3 (92 µg/m3). Thessaloniki had the highest grey space (98%) and Łódź the highest cumulative amount of pollen (39,041 p/m3). The highest daily noise levels ≥ 55 dB was in Reus (81% to traffic) and Regensburg (21% to railway). In drinking water, arsenic had the highest value in Thessaloniki (6.4 µg/L), boron in Celje (24 mg/L) and lead in Paris (46.7 µg/L). Portugal and Greece showed the highest pesticide residues in food (7%). In conclusion, utilizing open-access databases enables the translation of research findings into actionable strategies for public health interventions.


Study design
An observational cross-sectional study has been undertaken to further implement EDMS with data on exposure to external non-specific and specific exposome.

Study cities/countries
The HEALS project (2013-2019) integrated a comprehensive array of novel technologies, data analysis and modelling tools for supporting exposome-health association studies in a European birth cohort from ten European cities initiated in the frame of the Exposure and Health Examination Survey (EXHES): Celje (Slovenia), Łódź (Poland), Manchester (United Kingdom, UK), Palermo (Italy), Paris (France), Porto (Portugal), Regensburg (Germany), Reus (Spain), Rijeka (Croatia), Thessaloniki (Greece).These cities were chosen to represent different European meteo-climatic, geographical, geological, cultural, and behavioural characteristics (Fig. 1).
The EarlyFOOD project (2018-2022) investigated the external and internal exposome (metabolomics and microbiomics) for better understanding the development of asthma and allergies, obesity, diabetes and neurodevelopmental disorders.It involved birth cohorts from Palermo, Paris, and Reus, also participating in the HEALS study (Fig. 1).
Within the HEALS project, an EDMS, gathering information on environmental stressors (e.g.environmental pollution, food, bio-contaminants) in the ten cities participating in EXHES, was developed.Furthermore, within EarlyFOOD project, the EDMS was enriched with lifestyle, additional environmental stressors, and socio-economic characteristics for 2017-2020.
Due to the SARS-CoV-2 pandemic restrictions, the year 2020 is an outlier in relation to the considered stressors, thus it was decided to analyse it separately, wherever possible.

Socio-demographic characteristics
Table 1 shows socio-demographic characteristics stratified by city.Paris was the city with the highest total mean population (n = 2,168,614), and overall females overcome males (average across cities: 52% vs. 48%).In 2017-2019, the highest mortality rate was registered in Łódź, Porto and Rijeka (14%) and the highest mean Table 1.External non-specific exposome factors between 2017 and 2020 in the ten cities contributing to HEALS and EarlyFOOD projects.*Data at country level; NA: Not Available, data information not provided; NR: Not Reliable, data were available but insufficient data coverage; a prefecture; b province; c computed over two years before and the current year; d estimation for 2019-20 not definitive; BMI: Body Mass Index; °C: Celsius degree.www.nature.com/scientificreports/percentage of the population at risk of poverty was in Spain (21%).In 2020, a general increase in the mortality rate was shown while risk of poverty slightly increased only in France (+ 1%).Life expectancy at birth was generally higher in Reus females (86 years) and Palermo males (81 years).

Lifestyle risk factors
Country lifestyle risk factors are reported in Table 1.In 2017 smoking prevalence was highest in Greece (37%), and a general decrease was shown in 2020, except for Greece and Croatia (+ 5% and + 1%, respectively).In 2019, the highest percentage of pre-obese (25 ≤ BMI < 30 kg/m 2 ) and obese (BMI ≥ 30 kg/m 2 ) population resulted in Croatia (41%) and the UK (28%).As regards alcohol consumption, the highest "every day" and "every week" consumption was in Portugal (21%) and France (34%), respectively.In contrast, the highest percentage of "never" alcohol consumption was in Croatia (38%).On the other hand, drug consumption was highest in Croatia (62% prescribed) and Poland (45% not prescribed).

Climatic parameters
As expected according to geographical location, the hottest and wettest cities were Palermo (19 °C) and Manchester (82%), respectively (Table 1).

Air quality
In 2017-2019, the cities with the highest value of air pollutants (µg/m 3 ) were: Thessaloniki for PM 10 (38), Łódź for PM 2.5 (25), Porto for NO 2 (62), and Rijeka for summer O 3 (92).In 2020 a general decrease in PM and NO 2 values was shown in all cities with available data, while there was not a specific uniform trend for O 3 (Table 2).

Food pesticides
In 2017-2019, the highest percentage of food pesticide residues (Maximum Residue Levels (MRLs)) was observed in Portugal (7%), and a general increasing in the values was shown in 2020 (Table 2).

Discussion
The exposome refers to the sum of all environmental exposures that an individual experiences throughout the lifetime.Building the exposome requires collecting and integrating data from a variety of sources, including personal monitoring devices, biomonitoring, and environmental monitoring.
This paper reports the accessibility and usability of Open Data on exposure to the external non-specific (socio-demographic and lifestyle risk factors, climatic parameters, LU/LC) and specific (air, water and noise pollution, pollen/spores, food pesticides) exposome in 10 European cities/countries participating in the HEALS and EarlyFOOD projects.
Vol:.( 1234567890 Socio-economic status and lifestyle are significant determinants of children's health and wellbeing 11 .The results showed that Poland, UK and Croatia had lower life expectancies and higher rates of pre-obesity/obesity.It is well-known that a higher BMI in childhood and adolescence is associated with adverse health consequences throughout the lifespan 12 .Also, in Croatia and Poland, the higher consumption of drugs represented a potential higher morbidity risk for new generations.Children living in western-central Europe might be at higher poverty risk and be more susceptible to indirect consequences of high parental alcohol consumption, such as abandonment and violence 11 .Given the high smoking prevalence rates, France, Greece, and Croatia displayed a likely higher prevalence of Environmental Tobacco Smoking.Fetal exposure to tobacco and alcohol increases the risk of adverse pregnancy outcomes and other health problems in the life course, such as obesity 11 . As regards environmental risk factors, the high pollen load in Łódź and PM concentration in Łódź and Thessaloniki could increase the risk for children respiratory health and allergic sensitization 13 .Porto and Rijeka could expose children to a higher level of gaseous pollutants.Regarding urbanization, children of Thessaloniki lived in a highly urbanized city.Pollen is often at the origin of rhinitis and asthma 2,13,14 .Air pollution is a significant public health problem and urbanization is firmly correlated to air pollution 15,16 .Recent Italian studies showed that grey spaces are related to adverse effects on children and adults allergic status and PAHs exposure in adulthood 17,18 .The beneficial influence of green space was shown for wellbeing, diastolic blood pressure, salivary cortisol, heart rate, incidence of diabetes, and total and cardiovascular mortality 19,20 .Meanwhile, a recent meta-analysis found that green space exposure is a risk factor for childhood wheeze, asthma, and allergic rhinitis 21 .Other studies have highlighted how urban green areas enhance human wellbeing by providing ecosystem services absent in grey areas.These include improving air quality, offering recreational opportunities, and enriching cultural experiences [22][23][24] .Additionally, green areas contribute to regulating local temperatures, reducing the urban heat island effect, and moderating adverse natural events like floods 22,25 .The latter are particularly important in light of potential changes in meteorological patterns, such as heat waves and extreme events, resulting from climate change 26 .European children and especially in the "climatic hot spot" of the Mediterranean area, will live in increasingly hot climates, with persistent heat waves.Substantial and abrupt variations in temperatures are related to detrimental health effects, such as increasing total mortality and allergic morbidity 2,25,26 .Furthermore, the rising temperature and carbon dioxide concentrations may impact on pollen allergenicity, seasonality, distribution, and load, thus increasing pollen exposure 13,14,26 .It is also supposed that higher temperatures are associated with faster rates of fungal growth (but with fewer spores) and that extreme events could increase indoor dampness and consequent fungal proliferation 2 .These changes, ultimately, might affect children's allergic and respiratory health 2 .
Less known factors were also considered.Although likely underestimated, chronic exposure to noise pollution negatively impacts physical and mental health and wellbeing.It has been estimated that 113 million people are exposed to Lden of at least 55 dB from traffic and 22 million from railways in Europe 27 .Safe drinking water is a fundamental human right and it is essential to health, especially for the most vulnerable categories, such as infants, children, elderly and frail people 28 .The increasing frequency and severity of droughts may affect both the quality and quantity of water 28 .Lead exposure was associated with neurodevelopmental disorders, impaired renal function, hypertension, impaired fertility, adverse pregnancy outcomes, and mortality 28 .Animal studies showed a likely toxic effect on male reproductive tract of boron compounds exposure 28 .Even bacterial contamination may be dangerous for human health.Short-term peaks in pathogen concentration may considerably increase disease risks and expose the community to the risk of intestinal and other infectious disease outbreaks 28 .
Using plant protection products on crops or food products may result in pesticides residues in food, potentially posing a risk to public health 29 .To ensure a high level of consumer protection, Regulation (EC) No 396/20,059 established a legal limit of 0.01 mg/kg (MRLs) 29 .The higher percentage of MRLs exceeding in Portugal and Greece than in other countries generates concerns, which need to be deepened 29 .

Comparison with EU and international limits
Currently, EU limits and WHO guidelines exist only for air pollution, noise and water parameters (Table 3).The differences between the EU air quality standards and the WHO recommended values have increased after the publication of the new WHO air quality guidelines (AQG) on September 22, 2021, indicating significantly lower levels than previous ones 30,31 .In the study period 2017-2019, the cities generally exceeded the PM and NO 2 annual reference values of WHO air quality guidelines, but not of EU limits (Fig. 2, Table 3).
Only Paris and Porto violate the NO 2 EU limits.Despite lacking a summer limit for O 3 , the WHO air quality guidelines provided a seasonal recommended value, consisting of the average daily maximum 8-h mean O 3 concentration in the six consecutive months with the highest average O 3 concentration (60 µg/m 3 ).Apart from Manchester, Paris and Porto, all the cities exceeded the O 3 recommended value, in 2017-2019.
The EU Directive 2002/49/EC established general high noise thresholds: 55 dB for Lden and 50 dB for Lnight.The WHO European office defined lower guidelines values, based on the evidence on health effects (Table 3) 32,33 .Since exposed population percentage was provided according to EU limits, it is only possible to evidence their exceeding in almost every city.
Regarding drinking water, the substances above the EU limit and/or the WHO guidelines were: the 2017-2019 lead in Paris and Thessaloniki; the 2020 boron, and chlorates and chlorites in Celje and Łódź, respectively 28,34 .The presence of lead may be due to corrosive water effects on household plumbing systems containing lead in pipes or from the connections service to homes 28 .The amount of lead dissolved in the plumbing system depends on several physicochemical water properties 28 .Boron presence depends on the surrounding geology and wastewater discharges 28 .Values exceeding WHO guidelines and EU limits value of Enterococci and Escherichia coli were www.nature.com/scientificreports/found in Porto drinking water.Celje drinking water had exceeded in Escherichia coli limits value, as well.The presence of bacteria in water is likely due to faecal contamination 28 .

SARS-CoV-2 pandemic effects
As expected, the average mortality in 2020 among the ten cities increased, probably due to SARS-CoV-2 pandemic.Overall, the Covid-19 pandemic affected urban air pollution, especially PM and NO 2 (Table 2).In Europe during Covid-19 lockdowns, road transport reductions caused a temporary drop in NO 2 annual mean concentrations, up to 25% in France, Italy and Spain 35 .During the first lockdown in April 2020, the traffic monitoring stations registered a NO 2 concentrations drop up to 70% 35 .However, the Covid-19 lockdown measures' impact on the annual mean level of PM 10 and PM 2.5 was limited, and no greater than a median reduction of 4% and 5% across all stations, respectively 35 .This may be because increased emissions from residential heating could have counterbalanced reductions in other sectors 35 .

Usefulness and feasibility
The EDMS has been implemented to provide an informative, interactive, user-friendly tool to support the scientific community and stakeholders in environmental-health studies and environmental policies.Recently, a growing interest in the role of the external exposome in disease development has led to an increasing number of studies on this topic 4,5 .The challenge remains finding and processing of these different data.In this paper, all the possible data that could be recovered, regarding external non-specific and specific exposome factors, has been archived.The added value of this work is that the EDMS can be further expanded and constantly updated to be used in other European settings dealing with lifetime external exposome.However, its effectiveness is hampered by several criticisms.The difficulties in building and implementing the EDMS ranged from finding the data source to heterogeneity in the used language.In the Supplementary Information (Tables S2-S4) data search issues and source links are detailed.
One of the major concerns experienced for retrieving most environmental and lifestyle factors is the lack of a centralized database at the European level.This leads to time consuming data searches in separate national or even local sites or reports.Language barriers further exacerbate this issue, as many databases and reports are only accessible in the native language, thus requiring extensive translation efforts.Additionally, on web platforms exclusively in the native language, direct translation features within browsers were not always accessible, further complicating the translation process.Consequently, this linguistic harmonization has significantly consumed both time and staff resources, decreasing operational efficiency and productivity.Furthermore, the availability of reports rather than databases has necessitated manual extraction of data, so increasing the risk of human error and further prolonging the data retrieval process.
Another critical issue was the lack of standardization in reporting the data (e.g.different temporal resolution, parameters, unit of measures, etc.), which did not allow appropriate comparability of the various exposome factors among countries/cities.
Notwithstanding the existence of the climatic, air and noise pollution, and LU/LC European centralized databases (ECA&D, EEA and Copernicus databases), data for each of the ten studied cities were not always available.In many cases, data had insufficient coverage and therefore were unusable.In particular, this problem arose in air pollution data.The failure of European oversight of data supply, availability and quality or non-compliance of countries with European indications/regulations, results in a severe gap for multi-centre studies in this sector.
In addition, even if available, data did not completely cover the study period, weighting on the estimates of the various indicators.This aspect highlights Europe's digital gap, which is expected to increase without faster and  Although the EU encourages the implementation of Open Data, and the adoption of the FAIR data principle, according to which data have to meet principles of findability, accessibility, interoperability, and reusability, public data availability remains limited 10 .Indeed, we have found the lower availability for open pollen data in most of the European countries in this paper.A public consultation of pollen data would be necessary in a world of increasing allergic population 13 .
Finally, regarding drinking water, not all parameters regulated by the European Union are provided in the local reports/databases, whereas it is the citizen's right to exhaustively know the most important characteristics of the supplied water.
Overall, Open Access datasets provide ecological data.In epidemiology, ecological studies are used to understand the relationship between health outcome and exposure at a population level, where the population represents a group of individuals with shared characteristics such as geography, ethnicity and socio-economic status.Ecologic studies are more often subject to confounding bias than analytic risk studies due to the lack of information on potential confounders.However, mixing specific and generic exposome can reduce such confounding bias.
In summary, the limitations in data accessibility, standardization, and spatial and temporal coverage pose significant challenges.Addressing these issues is crucial for enhancing the effectiveness of EDMS, enabling the integration of additional data on factors like pollution and socio-economic status.Our study was limited to a descriptive analysis, lacking statistical inferences and validation of the tool's effectiveness.Consequently, further research on the application of EDMS in environmental epidemiology is warranted.Nevertheless, we believe EDMS can be an excellent tool to support ecological studies by centralizing all exposures within a unified database.This not only streamlines researchers' efforts but also enhances the precision of exposome estimations.By overcoming data heterogeneity and enhancing spatial resolution of data, EDMS would facilitate comparisons of exposomes across various European populations, thereby aiding in the identification of population-specific risk factors.Consequently, policymakers are empowered to make prompt evidence-based decisions to mitigate the public health burden.

Conclusions
We assessed external exposome by implementing an Environmental Data Management System, the EDMS, in ten European cities for the first time, ensuring the accessibility and the usability of data.As expected, a wide heterogeneity of risk factors exposures was shown across cities, highlighting some critical public health issues.From our study emerged the potential of standardized data management systems to facilitate interdisciplinary collaboration and data-driven decision-making in public health.Leveraging Open-Access databases for health research can yield numerous public health benefits including enhanced accessibility, accelerated discovery, transparency and reproducibility, cost-effectiveness, long-term sustainability, and finally ethical considerations (data sharing practices, research benefits equitably distributed across diverse populations).In conclusion, by harnessing these data management systems, we can address critical public health issues and pave the way for tailored preventive measures at the population level, thus ensuring a healthier future for generations to come.

Table 2 .
External specific exposome factors between 2017 and 2020 in the ten cities contributing to HEALS and EarlyFOOD projects.*Dataat country level; NA: Not Available, data information not provided; NR: Not Reliable, data were available but insufficient data coverage; ND: Not detected; PM 10 : particulate matter with an aerodynamic diameter smaller than 10 µm; PM 2.5 : particulate matter with an aerodynamic diameter smaller than 2.5 µm; NO 2 : Nitrogen Dioxide; O 3 : Ozone; µg/m 3 : microgram/cubic meter; p/m 3 : pollen/cubic meter;Through the EDMS, inter-cities differences in demographic and environmental aspects have emerged which could affect children's development.

Table 3 .
References value from European Union Directive (EU) and international guidelines (WHO).a average of daily maximum 8-h mean O 3 concentration in the six consecutive months with the highest running-average O 3 concentration; b referred to the precedent edition of WHO Guideline value; *no limit value but general thresholds indicating high noise levels; references in bibliography.Empty cells indicate that the guideline value was not provided.
more comprehensive engagement in Artificial Intelligence (AI) technologies, especially in European countries with relatively low AI facilities.